Engineering Commons^™

Analysing Sound Characteristics Of Cello And Violin Using Fast Fourier Transform, Sinin Hamdan, Khairul Anwar Mohamad Said, Ahmad Faudzi Musib, Marini Sawawi, Aaliyawani Ezzerin Sinin

ASEAN Journal on Science and Technology for Development

The unique sound characteristics of music are based on multiple harmonic frequencies that exist within the sound waves. Through Fast Fourier Transform (FFT) software, the wave can be broken down into frequency and amplitude components. Spectrum analysis can be used quantitatively to describe these sound characteristics. In this paper, the frequency range present in the spectrum and the average intensity of the first 10 high notes in the sound are used to classify the sound characteristics of the cello and violin. This is done by generating a frequency (x-axis) and amplitude (y-axis) graph for the sounds of the cello and …

Sustainable Flight Training Schools And Their Role To Meet Net Zero Targets, Eva Maleviti

Sustainability Conference

This presentation is part of a wider research project to identify the elements that must be considered regarding flight training schools’ role in aviation sustainability. Net Zero Pathways and goals, emission schemes, design specifications, and sustainable fuels are some of the most popular changes for airlines and manufacturers. Flight training schools must be at the forefront of promoting aviation sustainability to tomorrow’s professionals. The ICAO Carbon Offsetting Requirement Scheme for International Airlines (CORSIA) relies heavily on the firm and reliable information in the operators’ system. Proper emission calculation requires flight crews to feed valid and accurate flight information data. Hence, …

Designing Customized Loss Functions For Training Deep Neural Networks, Ali Pourramezan Fard

Electronic Theses and Dissertations

This dissertation explores the critical role of loss functions in enhancing the predictive performance of deep machine learning models. Loss functions are an integral element of all the ongoing advances we witness daily in this domain. I design custom loss functions and their impacts on various machine learning tasks, particularly in computer vision.

In the first stage of my research, I aim to improve the prediction performance of deep learning models by providing them with more precise feedback associated with task requirements. This led me to create the concept of assistive loss functions. My first proposed loss function, inspired by …

The Impact Of Cumulative And Acute Loading On Achilles Tendon Health, Performance, And Reported Pain In Collegiate Gymnasts, Julio Serrano Samayoa

Electronic Theses and Dissertations

Gymnasts are at a high risk of Achilles tendon (AT) injuries due to intense loads during takeoffs and landings. To better understand better the relationship between impact loading and its effects on tendon adaptation and athletic performance, this study uses Inertial Measurement Units (IMUs) to track AT loading across a collegiate gymnastics season. This data were compared against physiological and athletic performance metrics, obtained through force plates and ultrasound imaging, to explore how mechanical load influences reported pain and athletic performance. Results varied, with cumulative impacts being correlated with improved jump height (Spearman 0.362, Pearson 0.348), while peak power and …

Security Vulnerabilities In Mobile Operating Systems Used In Iot Devices: An Examination Of Current Challenges And Countermeasures, Isain Cortes Jr.

Cybersecurity Undergraduate Research Showcase

No abstract provided.

Autonomous Driving Trajectory Prediction, Carlos Funes

Undergraduate Research Symposium Lightning Talks

Autonomous driving is undoubtedly one of the world's most revolutionary technologies, opening the door to a more secure traffic environment. This innovation has led to vehicles being able to drive by themselves without the necessity of a person behind the wheel, as well as cruise control, lane-keeping assist, and automatic emergency braking. Unfortunately, there is still plenty of work before autonomous driving becomes more popular among drivers. While at UNLV as an undergraduate student/research assistant, one of my goals is to learn how these technologies work to bring ideas into the automotive industry by refining solutions to problems within these …

It's Not As Bad As You Think: Detecting Ai-Generated Voices, Yong Qin Xu

Undergraduate Research Symposium Lightning Talks

Advances in machine learning have opened up the world to a brand new frontier of fraudulent phone calls which the average person may not be in any way prepared for. From imitations of a loved one's voice to lifelike mimicry of human callers, telephone scams may become harder than ever to anticipate or prevent now that criminals have the help of AI on their side. This is why in my research paper, I aim to analyze and compare two existing methods of detecting the authenticity of human voice recordings in order to demonstrate and explain currently available technology that's capable …

Utilizing A Hybrid Apprach To Link Maternal And Neonatal Records, Vidhani S. Goel, Ana Reyes, Bertille Assoumou, Dodds P. Simangan, Farooq Abdulla, Megumi Akiyama, Deborah A. Kuhls, Kavita Batra

Undergraduate Research Symposium Posters

Linkage of independent datasets allows comprehensive and robust analysis. This study aims to utilize a hybrid strategy to link maternal records with neonatal data with an overarching goal of investigating correlates of adverse birth outcomes.

To link 126,757 records from Nevada Medicaid with 249,181 maternal records from Birth Registry, a hybrid linkage approach was utilized. Data normalization was first performed for the standardization of linkage keys. First, a deterministic approach was used to link these records using a unique identifier followed by a fuzzy or probabilistic algorithm using a set of block variables. These block variables included date of birth, …

Characterizing The Mechanical And Visoelastic Properties Of Sodium Alginate, Vesper Evereux

Undergraduate Research Symposium Posters

A crucial part of tissue engineering lies in understanding and characterizing the mechanical and viscoelastic properties of various types of biomaterials. Understanding these properties allows better biomaterials to be produced with characteristics more similar to those of the human body and with better biocompatability. In this study, sodium alginate was chemically crosslinked with calcium chloride and subsequently tested for it's instantaneous Elastic Modulus, instantaneous Shear Modulus, and equivalent viscosity using indentation testing methods consisting of a stress-relaxation test and nonlinear curve-fitting analysis. Two and three millimeter indentation tests were performed using a low-cost and portable device built in-lab that resulted …

Detection Of Methane Leaks By The Use Of Mid-Range Infrared Camera, Jared Rosario, Oscar Salcido

Undergraduate Research Symposium Posters

Timely detection of methane leaks from natural gas infrastructure, like pipelines and valves, is essential for mitigating environmental and safety risks. This research focuses on using mid-wave infrared (MwIR) cameras on unmanned aerial systems (UAS) to detect leaks. By leveraging machine learning, the study aims to develop an efficient, real-time methane inspection system that operates directly on embedded processors on UAS platforms.

This project employs the FLIR G300a OGI camera for remote gas inspection, utilizing video preprocessing and optical flow to mask gas plumes in footage. The YOLOv8 deep learning model is used to detect gas pixels and segment the …

Biochar/Hydrochar Applications In Disinfection Byproduct Removal For Drinking Water, Ashleu Mussio Marquez, Donna Rouhani, Ismail Abdulraheem, Kers Ung-Watson, Ahmadreza Khatamgooya, Scarlet Nelson, Dr. Jaeyun Moon, Dr. Erica Marti

Undergraduate Research Symposium Posters

This project aims to investigate the process of disinfection byproduct (DBP) removal in drinking water, looking into the applications of biochar and hydrochar, which are low cost and environmentally sustainable adsorbents. These carbon-based adsorbents are derived from agricultural waste biomass, such as walnut shells. These adsorbents will be used to capture and remove contaminants in water, such as DBPs. DBPs are formed when chemical disinfectants react with organic and inorganic substances naturally present in water. The targeted DBPs for adsorption include trihalomethanes, haloacetic acids, haloacetonitriles, and nitrosamines. An example of high concentration DBP formation is during emergency chlorination, where excess …

Smartphone Haptics Can Uncover Differences In Touch Interactions Between Asd And Neurotypicals, Ivonne Monarca, Franceli L. Cibrian, Isabel López Hurtado, Monica Tentori

Engineering Faculty Articles and Research

Utilizing touch interactions from smartphones for gathering data and identifying digital markers for screening and monitoring neurological disorders, such as Autism Spectrum Disorder (ASD), is an emerging area of research. Smartphones provide multiple benefits for this kind of study, including unobtrusive data collection via built-in sensors, integrated haptic feedback systems, and the capability to create specialized applications. Acknowledging the significant yet understudied presence of tactile processing differences in individuals with ASD, we designed and developed Feel and Touch, a mobile game that leverages the haptic capabilities of smartphones. This game provides vibrotactile feedback in response to touch interactions and collects …

Unleaded Fuel For General Aviation, Carolina Anderson, Laura Garcia

Sustainability Conference

The Clean Air Act, passed in the late 1970s, mandating the removal of lead from most fuels due its detrimental effects on public health, yet piston-driven aircraft continue to rely on leaded aviation gas (AvGas 100LL). This fuel remains the last lead-containing fuel regulated by the Department of Transportation (DOT). Lead, added as tetraethyl lead (TEL), enhances octane levels and prevents engine detonation, vital for high-compression aircraft engines. In response to the health effects, regulating bodies like the Environmental Protection Agency (EPA) have tightened lead standards and are assessing the risk posed by AvGas. Research links even low-level lead exposure …

Novel Nanocomposite Of Carbonized Chitosan-Zinc Oxide-Magnetite For Adsorption Of Toxic Elements From Aqueous Solutions, Dalia A. Ali Eng, Ganna Gaber Ismail Eng.

Chemical Engineering

Herein, a novel nanocomposite (carbonized chitosan-zinc oxide-magnetite, CCZF) was developed to effectively remove toxic elements in water remediation. Combining the high adsorption capacities of chitosan with the magnetic properties of magnetite and the chemical stability of zinc oxide, the combination of these unique properties makes it an efficient and versatile material that offers a sustainable solution for water purification. The (CCZF) nanocomposite was synthesized through the coprecipitation method and characterized using various techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), Brunauer–Emmett–Teller (BET) analysis, X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and zeta potential analysis. The results showed …

Ptsd Increases Risk For Hypertension Development Through Pvn Activation And Vascular Dysfunction In Sprague Dawley Rats, Xinqian Chen, Xin Yan, Chunxiu Yu, Qing-Hui Chen, Lanrong Bi, Zhiying Shan

Michigan Tech Publications

This study investigates the impact of single prolonged stress (SPS), a model of post-traumatic stress disorder (PTSD), on cardiovascular responses, hypothalamic paraventricular nucleus (PVN) activity, and vascular function to elucidate the mechanisms linking traumatic stress to hypertension. Although SPS did not directly cause chronic hypertension in male Sprague Dawley (SD) rats, it induced acute but transient increases in blood pressure and heart rate and significantly altered the expression of hypertension-associated genes, such as vasopressin, angiotensin II type 1 receptor (AT1R), and FOSL1 in the PVN. Notably, mitochondrial reactive oxygen species (mtROS) were predominantly elevated in the pre-autonomic regions of the …

Disciplinary Policy Research On Science Development Strategies For Crewed Lunar Exploration, Wei Yang, Yuyang He, Jinting Kang, Ruiyi Chen, Huihong Cheng, Li Sun, Pan Deng, Yong Wei, Yangting Lin, Xianhua Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

In order to better serve China’s crewed lunar exploration, this study researched and analyzed the current status of lunar exploration and planetary science research in China and the United States. Additionally, we conducted interviews and a questionnaire survey with experts in planetary science and deep-space exploration, and formed the following four policy recommendations: 1) Strengthening the layout and management of the disciplines of lunar and planetary sciences, and setting up a long-term and stable funding mechanism; 2) Improving the system of talent cultivation, and encouraging young talents to participate in deep-space exploration missions; 3) Strengthening the protection of original ideas, …

Benefits And Challenges Of Constructing Low-Altitude Air Route Network Infrastructure For Developing Low-Altitude Economy, Xiaohan Liao, Chenchen Xu, Huping Ye

Bulletin of Chinese Academy of Sciences (Chinese Version)

Low-altitude airspace is a resource that needs to be fully explored, and the low-altitude economy is a new type of economic activity resulted from low-altitude airspace exploration and utilization. As the primary players of low-altitude flight activities, the commercialization and wide applications of unmanned aerial vehicles (UAVs) are promoting the prosperity of the low-altitude economy. A low-altitude air route network is an effective means to ensure the safe and efficient operations of a large number of UAVs, and it is also a new key infrastructure hosting low-altitude traffic. The history shows that the investment on public transport infrastructure as a …

Strategies To Alleviate Flickering: Bayesian And Smoothing Methods For Deep Learning Classification In Video, Noah Miller, Glen Ryan Drumm, Lance Champagne, Bruce A. Cox, Trevor Bihl

Faculty Publications

Excerpt: Increasing reliance on autonomous systems requires confidence in the accuracies produced from computer vision classification algorithms. Computer vision (CV) for video classification provides phenomenal abilities, but it often suffers from “flickering” of results. Flickering occurs when the CV algorithm switches between declared classes over successive frames. Such behavior causes a loss of trust and confidence in their operations.

Integrating Humanities Into Cybersecurity Education: Enhancing Ethical, Historical, And Sociopolitical Understanding In Technical Training, Joseph Frusci

Journal of Cybersecurity Education, Research and Practice

The increasing complexity of cybersecurity challenges necessitates a holistic educational approach that integrates both technical skills and humanistic perspectives. This article examines the importance of infusing humanities disciplines such as history, ethics, political science, sociology, law, and anthropology—into cybersecurity education. Through a pilot course developed for Staten Island Technical High School, aligned with the New York State K-12 Computer Science and Digital Fluency Standards, students were introduced to an interdisciplinary curriculum that combined technical cybersecurity training with historical analysis, ethical reasoning, and sociopolitical context. The results of pre- and post-course assessments demonstrated significant improvements in critical thinking, ethical decision-making, and …

11.18.2024 Orsp Connect, Liz Williamson

ORED Newsletter

Director of Research Lab Safety

GIS Day

Tech Startup Weekend

NSF Virtual Grants Conference

Understanding The Plastic Issue (Poster Presentation), Regan Bossie, Peter Nguyen, John Mcswiggin, Adam Meadows

Sustainability Conference

The Plastic-Free Campus Initiative is an Embry-Riddle initiative advocating for the reduction and elimination of single-use plastics on the Daytona Beach campus.

Our poster presentation aims to highlight current issues and concerns by presenting plastic production trends, quantifying how plastic pollution has affected global ecosystems, and discussing the material characteristics of plastics and their consequences. The poster will provide an overview of the current state of global recycling and will outline key concerns that microplastics, and plastics in general, pose to public health. By presenting the current facts and concerns related to plastic and recycling, we hope to encourage individuals …

Computational Design Of Complex Concentrated Alloys, Hamid Sharifi

Doctoral Dissertations

A high-throughput parameterization of modified embedded atom model (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn was carried out using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics. Utilizing the MEAM interatomic potentials and a Monte Carlo scheme, phase segregation in the CrNiCo, CuNiCr and CuNiCo fcc alloys …

Machine Learning-Driven Process Analysis And Optimization In Solid-State Welding And Fusion-Based Additive Manufacturing, Radif Uddin Ahmed

Master's Theses

In the modern era of advanced manufacturing, optimizing process parameters is pivotal in ensuring the quality and reliability of sophisticated component fabrication. This study presents a novel, data-driven approach to parameter optimization in two cutting-edge manufacturing techniques: Friction Stir Welding (FSW) and Laser Powder Bed Fusion (LPBF). By leveraging machine learning methodologies, this research addresses the critical challenge of efficiently determining optimal process parameters, a task traditionally relying on time-consuming and resource-intensive trial-and-error methods. This study will lead to a robust data-driven framework for process analysis of more advanced manufacturing techniques like the Additive Friction Stir Deposition (AFSD) process. Friction …

The Santa Clara, 2024-11-15, Santa Clara University

The Santa Clara

No abstract provided.

Robotic Multi-Object Grasping From A Pile: Techniques And Algorithms For Enhanced Dexterity, Tianze Chen

USF Tampa Graduate Theses and Dissertations

As robots become increasingly integrated into real-world applications such as warehousing, fulfillment centers, and manufacturing, the need for efficient and adaptable robotic systems grows. One of the key challenges is enabling robots to grasp multiple objects simultaneously, as this significantly boosts the efficiency of tasks like batch picking, sorting, and object transferring, reducing both time and energy consumption. This dissertation presents a comprehensive multi-object grasping (MOG) pipeline that includes pre-grasp selection, end-pose selection, grasping synergy calculation, and a data-driven model for estimating the number of objects being grasped. Central to this work is the development of the Experience Forest structure, …

A Method For Key Node Identification In Operational Target System Based On War Gaming, Yongfu Zhang, Yang Liu, He Yuan

Journal of System Simulation

Abstract: The identification of key nodes in an operational target system is an important basis for combat command decision-making. Due to the lack of experimental verification of key node identification in the current operational target system in a campaign-level dynamic confrontation environment, a complex network model of operational target system with large-scale entities and complex interaction relationship was constructed by taking integrated air defense network as an example, with the help of the data derived from the large joint war gaming; the characteristics of wargame data were considered, and the value characteristics of combat targets and network structure characteristics were …

Platform Path Optimization Method Based On Cumulative Detection Probability Of Sonar Search, Xiang Wei, Xingxuan Liu, Dianzheng Fu, Tianji Yang, Jiaxuan Yang

Journal of System Simulation

Abstract: To address the lack of research on the optimal path of mobile search platform to search for moving targets, this paper proposes a path optimization method of mobile search platform based on cumulative search probability theory. Based on the cumulative detection probability (CDP), one of the important criteria of sensor performance evaluation, a single-peak CDP calculation formula is constructed by using a time series correlation model, namely the (λ, σ) process model. A set of target motion scenarios are constructed, and the trajectory probability of target scenarios and their CDP at different time are corrected by Bayesian posterior probability. …

Modeling For Decision Support Of Flight Ground Support Process, Zhiwei Xing, Ruiwen Yu, Biao Li, Zhaoxin Chen

Journal of System Simulation

Abstract: Aiming at the problems of insufficient decision-making ability and low operational efficiency of the flight ground support process, a decision support model of the flight ground support process based on the department of defense architecture framework (DoDAF) is proposed. Starting from the support operation, support resources, and the relationship between them, the quantitative description of the flight ground support process is performed. DoDAF and the model-based systems engineering (MBSE) modeling method are combined to establish a decision support model of the flight ground support process. The decision utility function is established to analyze the utility value of the comprehensive …

End-To-End Motion Planning Of Unmanned Vehicles Based On Multimodal Deep Reinforcement Learning, Kaiyuan Ding, Askar Hamdulla, Bin Zhu, Eksan Firkat, Zhengtang Ma

Journal of System Simulation

Abstract: Since the agent cannot sense the surrounding environment and cannot successfully avoid obstacles, reinforcement learning fails to be generalized to robot motion planning in difficult terrain. Therefore, a solution based on multimodal deep reinforcement learning, which learns to blend proprioceptive states with high-dimensional depth sensor inputs, is proposed for the motion planning of unmanned vehicles. To be specific, proprioceptive states offer contact measurement for immediate reaction, and the unmanned vehicle can learn and forecast environmental changes with its attached visual sensors, proactively navigating around obstacles and uneven terrains numerous time steps ahead. TransProAct (transformer-based proactive action), a unique end-to-end …

Flexible Job Shop Scheduling Method Based On Collaborative Agent Reinforcement Learning Algorithm, Jian Li, Huankun Li, Pengbo He, Huabei Wang, Liping Xu, Kui He

Journal of System Simulation

Abstract: To enhance the efficiency of flexible job shop scheduling, this paper develops a Markov decision process with specific constraints tailored to the scheduling problem. A cooperative agent reinforcement learning method is proposed to solve the problem of concurrent selection of workpieces and machines. During the construction of the Markov decision process, a disjunctive graph is introduced to represent the state characteristics. Two agents are introduced to select the workpieces and machines. The reward parameters governing the entire scheduling process are established by predicting variations in the minimum-maximum completion time across different time points. A GIN(graph isomorphic network) graph neural …